The scheme is an interactive application based on a previously published taxonomy . It is based on three sections (or steps):
1) Motor skills. In this section, you should select the motor skill you are interested in evaluating. The skills are classified according to three features :
– Functional GOAL of the motor skill, classified in “Posture” or “Walking”
– Role of the ENVIRONMENT, classified in “Stationary” or “In Motion”
– Type of external DISTURBANCE, classified in “Constant” or “Variable”
This classification is particularly useful because it provides an indication on the complexity of the motor skill (i.e. posture is simpler than walking, static environment is simpler than a moving one, and constant disturbance is simpler than variable), therefore helpful in deciding which motor skill start to test/implement.
2) Benchmarks. This section includes a list of metrics (benchmarks) associated to the skill previously defined. Benchmarks are grouped in two main categories, which measure the two main facets of bipedal functions:
– PERFORMANCE focuses on the accomplishment of the functional goal, in terms of “Stability” (i.e. not falling) and “Efficiency” (i.e. low energetic costs), with no particular attention on how this is achieved.
– HUMAN LIKENESS focuses specifically on “how” the motor skill is accomplished with respect to healthy human reference. This category includes “kinematics” and “dynamic” features.
3) Filter. The third part of the scheme is the result of the previous two steps, returning a list of papers in which the selected benchmark has been applied in the selected motor skill. These papers can be of help to researchers in replicating the same method on a different bipedal system. In this part, we strongly encourage the community in proposing protocols that are easily replicable (see the section IMPROVE the scheme for details)
 Torricelli, D.; Gonzalez-Vargas, J.; Veneman, J.; Mombaur, K.; Tsagarakis, N.; del-Ama, A.; Gil-Agudo, A.; Moreno, J.; Pons, J., “Benchmarking Bipedal Locomotion: A Unified Scheme for Humanoids, Wearable Robots, and Humans,” in Robotics & Automation Magazine, IEEE, vol.22, no.3, pp.103-115, Sept. 2015. DOI: 10.1109/MRA.2015.244827 – Published version – Pre-print version
 A. M. Gentile, “Skill acquisition: Action, movement, and neuromotor processes,” in Movement Science: Foundations for Physical Therapy, 2000, pp. 93–154.